Indexing a year of video locally on a 2021 MacBook with Gemma4-31B (50GB swap)

> The skill is open at ~/.claude/skills/video-index/. If you're working on something similar (indexing personal archives, getting a local model to do real archival work, building agents that drive editing tools), I'd be glad to compare notes.

When your Claude wrote this post they might not have selected the right URL to share, unless your home folder is exposed. Care to share the skill files?

UPDATE: Quickly created a repo for this - https://github.com/Simbastack-hq/framedex (MIT License)

It's not tested properly after I genericized it. Will try to go through it properly and add more updates.

Two big things on my TODO: 1) Make use of this indexing and using Claude's help, make video editing faster with Davinci Resolve (now that I have a good index of all the content)

2) I currently did this for videos, but I want to add more things to this for my thousands of still images of my camera - need to make sense of them. So I'll be working on this as well.

Two questions:

1. What is the search index?

2. The "description.md" example has things like "faces -> cluster_id". Is this from Davinci Resolve's face index? Things like faces+names and locations are really important with photo collections, but general LLMs don't handle them so well.

I’d like to do something like this for the collection of home videos I have piling up, but I’m still on 16GB M1. Any hope of getting decent results with smaller models? If not, does anyone have tips on GPU rental?

I have a Claude max sub and plenty of OpenRouter credit, but I don’t feel good about uploading my family’s private videos

My take is that B2C AI applications are kind of structurally limited by how hard it is to build personalized context.

The idea of capable local models could be a huge unlock here if they are able to do the bottom-up context collection research / tagging / etc. at scale.

I ran Gemma on a 2015 thinkpad to do something similar. Fortunately, I could upgrade the memory otherwise it would have been a painful exercise.

Not gonna lie, llama.cpp had the fans spinning at max speed. But it worked and I got the job done.

> generative AI video has no place on a real travel brand

I am pretty sure that the vast majority of Airbnb hosts would not agree with you.

> equals TripAdvisor crucifixion

I have no idea how the Airbnb hosts with fake listings survive, really.

Thanks for the article! I have a beefy M5 Pro and I'm eagerly looking around for ways to use local models (specifically Gemma4 & Qwen3.6).

This is an excellent thing to do. Especially that LLMs excel at batching thus you can index multiple photos and videos in parallel for no performance penalty.

the reason 50GB swap is even viable here is Apple Silicon's memory bandwidth. on x86 that much swap would make inference unusably slow

Awesome. Say, this is very comprehensive.

I was vaguely aware of all these pieces existing (except for running a facial recognition database at home o_o), but it's really neat to put them all together like that.

Reading this text feels strange, sentences seems to be detached

Now I have another project for this weekend! I also have tons of video and not a lot of time to index them.

The subject matter is interesting but the amount of slop makes it difficult to read through. Yeah, it's great that you can throw your technical problems at Claude without caring much about the generated output but treating your own writing that you actually want to share with the world the same way is a terrible idea.

So do they run the lodge or what?

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